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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Object Detectors Emerge in Deep Scene CNNs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1412.6856/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1412.6856/feed.xml" rel="self" type="application/rss+xml" /><item><title>Object Detectors Emerge in Deep Scene CNNs — mentioned by jesuslop</title><link>https://news.ycombinator.com/item?id=12716118</link><guid isPermaLink="false">urn:hackerpapers:mention:1412.6856:12716118</guid><pubDate>Sat, 15 Oct 2016 23:31:49 GMT</pubDate><description>&lt;p&gt;In addition to the intro that I liked a lot, I find interesting, or even important, the usage of an unsupervised method to generate the visual symbolic dictionary, a convolutional autoencoder here. In arxiv:1412.6856 unsupervised object detectors emerge as byproducts in a CNN for another kind of task, for more interesting, photorealistic objects.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1412.6856/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
